System and method of providing reservation masks within a compute environment

ABSTRACT

A system, method and computer-readable media for providing a reservation mask for compute resources such as a cluster or a grid. The method aspect comprises identifying a need type and a group of available resources, creating a reservation mask over the identified group of resources and if a request from a consumer matches the need type, then constraining the creation of a reservation for the consumer to only use resources within the reservation mask.

PRIORITY CLAIM

The present application is a continuation of U.S. patent applicationSer. No. 11/629,940, filed Dec. 18, 2006, which is a 371 ofPCT/US2005/021427, filed Jun. 17, 2005, which claims priority to U.S.Provisional Application No. 60/581,257 filed Jun. 18, 2004, U.S.Provisional Application No. 60/552,653, filed Mar. 13, 2004 and U.S.Provisional Application No. 60/586,120, filed Jul. 7, 2004, the contentsof which are incorporated herein by reference.

BACKGROUND

1. Field of the Disclosure

The present invention relates to reservations in a compute environmentsuch as a cluster and more specifically to a system and method ofproviding reservation masks to manage resources in a computeenvironment.

2. Introduction

The present invention relates to a system and method of managing computeresources in the context of a grid or cluster of computers. Gridcomputing may be defined as coordinated resource sharing and problemsolving in dynamic, multi-institutional collaborations. Many computingprojects require much more computational power and resources than asingle computer or single processor may provide. Networked computerswith peripheral resources such as printers, scanners, I/O devices,storage disks, scientific devices and instruments, etc. may need to becoordinated and utilized to complete a task.

Grid/cluster resource management generally describes the process ofidentifying requirements, matching resources to applications, allocatingthose resources, and scheduling and monitoring grid resources over timein order to run cluster/grid applications or jobs as efficiently aspossible. Each project will utilize a different set of resources andthus is typically unique. In addition to the challenge of allocatingresources for a particular job, administrators also have difficultyobtaining a clear understanding of the resources available, the currentstatus of the cluster/grid and available resources, and real-timecompeting needs of various users. One aspect of this process is theability to reserve resources for a job. A cluster manager will seek toreserve a set of resources to enable the cluster to process a job at apromised quality of service.

General background information on clusters and grids may be found inseveral publications. See, e.g., Grid Resource Management, State of theArt and Future Trends, Jarek Nabrzyski, Jennifer M. Schopf, and JanWeglarz, Kluwer Academic Publishers, 2004; and Beowulf Cluster Computingwith Linux, edited by William Gropp, Ewing Lusk, and Thomas Sterling,Massachusetts Institute of Technology, 2003.

It is generally understood herein that the terms grid and cluster areinterchangeable in that there is no specific definition of either. Theterm compute environment may apply to a cluster, a grid or variations onthe general concepts of clusters or grids. The definition of a clusteror grid is very flexible and may refer to a number of differentconfigurations of computers. The introduction here is meant to begeneral given the variety of configurations that are possible. Ingeneral, a grid will comprise a plurality of clusters as will be shownin FIG. 1A. Several challenges exist when attempting to maximizeresources in a compute environment. First, there are typically multiplelayers of grid and cluster schedulers. A grid 100 may comprise a groupof clusters or a group of networked computers within a particularadministrative control. A grid scheduler 102 communicates with aplurality of cluster schedulers 104A, 104B and 104C. Each of thesecluster schedulers communicates with a respective resource manager 106A,106B or 106C. Each resource manager communicates with a respectiveseries of compute resources shown as nodes 108A, 108B, 108C in cluster110, nodes 108D, 108E, 108F in cluster 112 and nodes 108G, 108H, 1081 incluster 114.

Local schedulers (which may refer to either the cluster schedulers 104or the resource managers 106) are closer to the specific resources 108and may not allow grid schedulers 102 direct access to the resources.Examples of compute resources include data storage devices such as harddrives and computer processors. The grid level scheduler 102 typicallydoes not own or control the actual resources. Therefore, jobs aresubmitted from the high level grid-scheduler 102 to a local set ofresources with no more permissions that the user would have. Thisreduces efficiencies and can render the reservation process moredifficult.

The heterogeneous nature of the shared resources also causes a reductionin efficiency. Without dedicated access to a resource, the grid levelscheduler 102 is challenged with the high degree of variance andunpredictability in the capacity of the resources available for use.Most resources are shared among users and projects and each projectvaries from the other. The performance goals for projects differ. Gridresources are used to improve performance of an application but theresource owners and users have different performance goals: fromoptimizing the performance for a single application to getting the bestsystem throughput or minimizing response time. Local policies may alsoplay a role in performance.

Within a given cluster, there is only a concept of resource managementin space. An administrator can partition a cluster and identify a set ofresources to be dedicated to a particular purpose and another set ofresources can be dedicated to another purpose. In this regard, theresources are reserved in advance to process the job. There is currentlyno ability to identify a set of resources over a time frame for apurpose. By being constrained in space, the nodes 108A, 108B, 108C, ifthey need maintenance or for administrators to perform work orprovisioning on the nodes, have to be taken out of the system,fragmented permanently or partitioned permanently for special purposesor policies. If the administrator wants to dedicate them to particularusers, organizations or groups, the prior art method of resourcemanagement in space causes too much management overhead requiringconstant adjustment to the configuration of the cluster environment andalso losses in efficiency with the fragmentation associated with meetingparticular policies.

To manage the jobs submissions, a cluster scheduler will employreservations to insure that jobs will have the resources necessary forprocessing. FIG. 1B illustrates a cluster/node diagram for a cluster 110with nodes 120. Time is along the X axis. An access control list 114(ACL) to the cluster is static, meaning that the ACL is based on thecredentials of the person, group, account, class or quality of servicemaking the request or job submission to the cluster. The ACL 114determines what jobs get assigned to the cluster 110 via a reservation112 shown as spanning into two nodes of the cluster. Either the job canbe allocated to the cluster or it can't and the decision is determinedbased on who submits the job at submission time. The deficiency withthis approach is that there are situations in which organizations wouldlike to make resources available but only in such a way as to balance ormeet certain performance goals. Given the prior art model, companies areunable to have the needed or required flexibility over their clusterresources. To improve the management of cluster resources, what isneeded in the art is a method for a module associated withadministrative software that controls compute resources within a computeenvironment to manage reservations within the compute environment moreefficiently and with more flexibility.

SUMMARY

Additional features and advantages of the invention will be set forth inthe description which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. Thefeatures and advantages of the invention may be realized and obtained bymeans of the instruments and combinations particularly pointed out inthe appended claims. These and other features of the present inventionwill become more fully apparent from the following description andappended claims, or may be learned by the practice of the invention asset forth herein. The present invention addresses the need to manage thereservation process with more flexibility and efficiency. The inventionintroduces the concept of reservation masks and comprises a method,system, and a computer-readable medium for managing compute resources bycreating reservation masks over an identified group of computeresources. The method manages compute resources within a computeenvironment by identifying a need type and a group of available computeresources, creating a reservation mask over the identified group ofcompute resources and if a request from a consumer matches the needtype, then constraining the creation of a sub-reservation for theconsumer to only use compute resources within the reservation mask. Aset of reservation masks may be created as well, wherein multiplesub-reservations from multiple consumer requests will each beconstrained to only use compute resources within the set of reservationmasks. In one aspect of the invention, the mask is a policy-enforcingmechanism to manage and constrain reservations.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the invention can be obtained, a moreparticular description of the invention briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered to be limiting of its scope, the invention will bedescribed and explained with additional specificity and detail throughthe use of the accompanying drawings in which:

FIG. 1A illustrates generally a grid scheduler, cluster scheduler, andresource managers interacting with compute nodes;

FIG. 1B illustrates a job submitted to a resource set in a computingenvironment;

FIG. 2A illustrates a method of creating a reservation mask;

FIG. 2B illustrates a method of providing a roll-back reservation mask;

FIG. 2C illustrates a method embodiment of the invention;

FIG. 3A illustrates a reservation mask;

FIG. 3B illustrates another aspect of the reservation mask;

FIG. 4 illustrates a floating reservation; and

FIG. 5 illustrates another aspect of a roll-back reservation mask.

DETAILED DESCRIPTION

Various embodiments of the invention are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the invention.

The present invention relates to resource reservations in the context ofa compute environment. The environment may be operated by a hostingfacility, hosting center, a virtual hosting center, data center, grid,cluster and/or utility-based computing environments. The system aspectof the invention comprises a computing device that operates softwarethat practices the steps of the invention to manage compute resources.There are many known types of computing devices that are known to thoseof skill in the art and that are acceptable as the system embodiment ofthe invention. The computing device may be a single device or aplurality of connected computing devices that enable the invention to bepracticed. The software operating within the system is comprised ofcomputer program modules written in a computing language, such as the Cprogramming language or any other suitable programming language. Theprogramming modules include all the necessary programming to communicatewith the compute environment (i.e., such as the cluster/grid) and bothreceive information about the compute resources within the computeenvironment and also manage the reservation and use of those computeresources. The primary invention disclosed herein relates to the conceptof the reservation mask. Therefore, the system embodiment of theinvention will include the various modules that are configured tocontrol a processor to practice the steps of the method embodiment ofthe invention disclosed herein. For example, a system for managingcompute resources within a compute environment may comprise means foridentifying a need type and a group of available resources, means forcreating a reservation mask over the identified group of resources andmeans for constraining the creation of a sub-reservation associated witha request from a consumer that matches the need type. The means forperforming this may be, as mentioned above, computer programmed moduleswithin a software package that are configured to control the processorto perform these steps.

Prior to discussing the reservation masks according to the invention,some other explanatory information is provided about reservations andthe access control list.

The present invention allows the ACL for the reservation to have adynamic aspect instead of simply being based on who the requester is.The ACL decision making process is based at least in part on the currentlevel of service or response time that is being delivered to therequester. To illustrate the operation of the ACL, assume that a usersubmits a job and that the ACL reports that the only jobs that canaccess these resources are those that have a queue time that currentlyexceeds two hours. If the job has sat in the queue for two hours it willthen access the additional resources to prevent the queue time for theuser from increasing significantly beyond this time frame. The decisionto allocate these additional resources can be keyed off of utilizationof an expansion factor and other performance metrics of the job.

Whether or not an ACL is satisfied is typically and preferablydetermined by the scheduler 104A. However, there is no restriction inthe principle of the invention regarding where or on what node in thenetwork the process of making these allocation of resource decisionsoccurs. The scheduler 104A is able to monitor all aspects of the requestby looking at the current job inside the queue and how long it has satthere and what the response time target is and the scheduler itselfdetermines whether all requirements of the ACL are satisfied. Ifrequirements are satisfied, it releases the resources that are availableto the job. A job in the queue can then consume resources and thescheduler communicates this to the scheduler 104A. If resources areallocated, the job is taken from the queue and inserted into thereservation in the cluster.

An example benefit of this model is that it makes it significantlyeasier for a site to balance or provide guaranteed levels of service orconstant levels of service for key players or the general populace.Setting aside certain resources and only making them available to thejobs which threaten to violate their quality of service targetsincreases the probability of satisfying the targets.

The disclosure now continues to discuss reservations further. An advancereservation is the mechanism by which the present invention guaranteesthe availability of a set of resources at a particular time. With anadvanced reservation a site now has an ability to actually specify howthe scheduler should manage resources in both space and time. Everyreservation consists of three major components, a list of resources, atimeframe (a start and an end time during which it is active), and anaccess control list (ACL). These elements are subject to a set of rules.The ACL acts as a doorway determining who or what can actually utilizethe resources of the cluster. It is the job of the cluster scheduler tomake certain that the ACL is not violated during the reservation'slifetime (i.e., its timeframe) on the resources listed. The ACL governsaccess by the various users to the resources. The ACL does this bydetermining which of the jobs, various groups, accounts, jobs withspecial service levels, jobs with requests for specific resource typesor attributes and many different aspects of requests can actually comein and utilize the resources. With the ability to say that theseresources are reserved, the scheduler can then enforce true guaranteesand can enforce policies and enable dynamic administrative tasks tooccur. The system greatly increases in efficiency because there is noneed to partition the resources as was previously necessary and theadministrative overhead is reduced it terms of staff time because thingscan be automated and scheduled ahead of time and reserved.

As an example of a reservation, a reservation may specify that node002is reserved for user John Doe on Friday. The scheduler will thus beconstrained to make certain that only John Doe's jobs can use node002 atany time on Friday. Advance reservation technology enables many featuresincluding backfill, deadline based scheduling, QOS support, and metascheduling.

There are several reservation concepts that will be introduced asaspects of the invention. These include dynamic reservations,co-allocating reservation resources of different types, reservationsthat self-optimize in time, reservations that self-optimize in space,reservations rollbacks and reservation masks. The main focus of thepresent invention is the reservation mask.

Dynamic reservations are reservations that are able to be modified oncethey are created. Attributes of a reservation may change based on afeedback mechanism that adds intelligence as to ideal characteristics ofthe reservation and how it should be applied as the context of itsenvironment or an entities needs change. One example of a dynamicreservation is a reservation that provides for a guarantee of resourcesfor a project unless that project is not using the resources it has beengiven. A job associated with a reservation begins in a clusterenvironment. At a given portion of time into processing the job oncompute resources, the system receives compute resource usage feedbackrelative to the job. For example, a dynamic reservation policy may applywhich says that if the project does not use more than 25% of what it isguaranteed by the time that 50% of its time has expired, then, based onthe feedback, the system dynamically modifies the reservation ofresources to more closely match the job. In other words, the reservationdynamically adjust itself to reserve X % fewer resources for thisproject, thus freeing up unused resources for others to use.

Another dynamic reservation may perform the following step: if usage ofresources provided by a reservation is above 90% with fewer than 10minutes left in the reservation then the reservation will attempt to add10% more time to the end of the reservation to help ensure the projectis able to complete. In summary, it is the ability for a reservation toreceive manual or automatic feedback to an existing reservation in orderto have it more accurately match any given needs, whether those be ofthe submitting entity, the community of users, administrators, etc. Thedynamic reservation improves the state of the art by allowing the ACL tothe reservation to have a dynamic aspect instead of simply being basedon who the requestor is. The reservation can be based on a current levelof service or response time being delivered to the requestor.

Another example of a dynamic reservation is consider a user submitting ajob and the reservation may need an ACL that requires that the only jobthat can access these resources are those that have a queue time that iscurrently exceeded two hours. If the job has sat in the queue for twohours it will then access the additional resources to prevent the queuetime for the user from increasing significantly beyond this time frame.You can also key the dynamic reservation off of utilization, off of anexpansion factor and other performance metrics of the job.

The ACL and scheduler are able to monitor all aspects of the request bylooking at the current job inside the queue and how long it has satthere and what the response time target is. It is preferable, althoughnot required, that the scheduler itself determines whether allrequirements of the ACL are satisfied. If the requirements aresatisfied, the scheduler releases the resources that are available tothe job.

The benefit of this model is that it makes it significantly easier for asite to balance or provide guaranteed levels of service or constantlevels of service for key players or the general populace. Setting asidecertain resources and only making them available to the jobs whichthreaten to violate their quality of service target increases theprobability of satisfying those targets.

Another reservation type is a self optimizing reservation in time. Inmany cases, people will request resources and request that they beavailable at a particular time. For example, a person is doing ademonstration and it happens to be from 2:00 pm to 4:00 pm. In manyother cases, people will simply have a deadline or simply wantprocessing as early as possible. With a self-optimizing in timereservation, the scheduler is actually able to lock in a set ofresources for a particular request and then over time evaluate thecluster resources and determine if it can actually improve on it andimprove on the reservation in such a way as to guarantee that it doesnot lose the resources that it has already made available.

With self-optimizing reservations in time, a particular request may comein requesting resources that meet the following criteria but therequester prefers resources that meet a more increasingly strictcriteria. The scheduler, in finding the reservation, may be able tosatisfy the required criteria but not necessarily satisfy all thepreferred criteria. Over time, the scheduler, once it has established areservation that meets the minimum criteria, it can continue to look atnewly freed up resources and determine if it can, to a larger and largerextent, satisfy the preferred resource needs as well. This selfoptimizing reservation technology is also useful to work around resourcefailures in the case of a reservation that has already had reserved allthe resources it needs and it has a node failure. It can actuallycontinue to locate resources and reallocate resources that are still upand running and be able to satisfy the time frame it originally promisedby excluding the failed node and picking up a newly available computenode.

With the above concepts about reservations and the ACL in mind, thereservation mask is next introduced. FIG. 2A illustrates the steps takento provide a reservation mask for compute resources. The methodcomprises identifying a need type and a group of available resources(202), creating a reservation mask over the identified group ofresources (204) and if a request from a consumer matches the need type,then constraining the creation of a sub-reservation for the consumer toonly use resources within the reservation mask (206). The reservationmask therefore has a different purpose from the reservation itself. Themask is a policy-enforcing mechanism to manage and constrainreservations. Identifying a need type and a group of available resourcesmay be based on an administrative policy or some other criteria. Thesub-reservation may be constrained by independent, non-administrativecriteria, such as the quantity of resources and on a per-credentialbasis. For example, the constraints may limit each member of a group tosix processors at a time. If the request from a requestor matches theneed type, then the creation of the sub-reservation may be constrainedat least according to credentials associated with the request. Thecredentials may be at least one of: per user credential, per groupcredential, per class credential, quality of service-based credentialand a partition-based credential. There are preferably policies thatimpose these constraints upon the sub-reservations. These types ofindependent limits on non-administrative reservations do not really haveanything to do with the reservation mask but relate to the ability tolimit the creation of reservations with or without the masks accordingto the per-credential policy. In other words, the per person, per group,per class, per QOS, per partition, etc. policy that imposes theseconstraints. In this case, these constraints only apply to a personal ora grid reservation and not to administrative reservations.

The sub-reservation (or simply, the reservation) may be dynamicallymodified according to received data such as resource usage, systemperformance, a policy and a criterion associated with the request. Forexample, if resource usage is low, the sub-reservation may bedynamically modified to use 8 more processors which are not being usedto more efficiently use the resources and more quickly complete thetask. Such modifications may be bounded by minimum thresholds andmaximum thresholds such as load metrics or system performanceparameters. Modifying the sub-reservation may involve several things.For example, the ACL may be modified, the reserved resources may bemodified, and the time frame covered may be modified. Othermodifications may be made as well to further improve the completion ofthe task either from a job standpoint or a compute environmentstandpoint.

If a request from the consumer does not match the need type, then noconstraints are enforced for creating a reservation for the request fromthe consumer. Creating the reservation mask may also involve specifyingat least one timeframe during which the reservation mask enforcesconstraints, such as during business hours, eastern time. The time framemay also be a plurality of independent or periodic time frames. Themethod may also provide for specifying an access control list thatconstrains which consumers or resource requests may utilize resourceswithin the reservation mask. The request from the consumer or requestoris typically placed within the access control list. The need type mayrefer to a particular use, a user, a group of users, a job source, atype of job submission, personal reservation, grid reservation, clusterreservation and so forth.

A personal reservation, for example, may consist of a reservation thatdedicates resource access to a specific user or group of users. Oneaspect of the personal reservation or reservation from a consumer isthat is it is a non-administrator request. If the personal reservationprovides access to resources to a group of users, then each reservationand reservation timeframe are determined by a user in the group of usersthat requests the respective reservation. Where there are administratorrequests and personal requests that may be submitted, the administratorrequests may be different in one aspect in that they are not constrainedwithin the reservation mask. A grid reservation is a reservationrequested from outside an administrative group. When a grid reservationis received (a grid-based request) and established, the system protectsor guarantees the resource availability for a job that is remotelycreated from the local compute resources.

Another aspect of reservation relates to a roll-back reservation in timeor a roll-back reservation mask. FIG. 2B illustrates this methodembodiment of the present invention. The method of managing computeresources within a compute environment comprises establishing a policyto provide compute resources within a fixed time from the reception of arequest for a reservation (210), creating a roll-back reservation maskwhich slides ahead of current time by the fixed time (212) and receivinga request for a reservation (214). Upon receiving the request for areservation, the roll-back reservation mask insures that computeresources will be available for reservation within the fixed timeaccording to the policy. The policy may be established according to anagreement with a requestor of compute resources and the provider ormanager of the compute resources. An example policy would insure thatthe requestor of resources may be able to reserve and have at apredetermined quality of service, 100 nodes, 3 GB of memory and acertain bandwidth of communication within six hours of a request.

The compute environment is a cluster or a grid or any other grouping ofcompute devices or compute nodes. Within the roll-back reservation mask,the mask analyzes compute resources according to the policy to insurethat compute resources may be reserved by the requestor within the fixedperiod of time. An example of the request for a reservation is aconsumption request, where a user desires to process a submitted jobusing the compute resources. After receiving the reservation request,the roll-back reservation mask reserves the appropriate computeresources according to the request and the policy such that within thefixed amount of time, the requestor has access to his or her reservedresources.

The reservation mask can also be self-optimizing. Given that there issufficient time to analyze the request or reservation and the computeresources, the reservation mask may analyze whether a level of servicecan be improved for the reservation request and if the level of servicecan be improved, then the mask cancels the reservation of computeresources and reserves a second group of compute resources. The mask orsome other compute process may perform some of these steps. Thisself-optimization process of modifying or canceling and re-issuingreservations to improve performance of either the compute environment orthe quality of service delivered to the requestor may occur until apredetermined point. For example, assume the policy requires that therequestor have resources reserved and available for use within one hourof the request. If the requestor requests a reservation for three hoursinto the future, the roll-back reservation mask has two hours until thefixed guaranteed time to optimize the request. When the time comes wherethe request needs to be honored within one hour, one aspect of theinvention requires the reservation to be set and thus not “covered” bythe reservation mask. The reservation in this sense has slipped out fromunderneath the reservation mask. This is shown by the reservations 406in FIG. 4 and FIG. 5.

The roll-back reservation mask 402, 502 has a length preferably based onthe agreement. This may be, for example, a several months or it may beindefinite or of infinite length. Preferably, the length of the mask402, 502 is associated with how far into the future it analyzes computeresources and a height associated with a guaranteed throughput.

FIG. 3A illustrates a standing reservation. In cluster 302, there arestanding reservations shown as 304A, 304B and 304C. These reservationsshow resources allocated and reserved on a periodic basis. These areconsuming reservations meaning that cluster resources will be consumedby the reservation.

A reservation mask, mentioned above, allows a compute site to create“sandboxes” in which other guarantees can be made. The most commonaspects of this reservation are for grid environments and personalreservation environments. In a grid environment, a remote entity will berequesting resources and will want to use these resources on anautonomous cluster for the autonomous cluster to participate. In manycases it will want to constrain when and where the entities can reserveor utilize resources. One way of doing that is via the reservation mask.

FIG. 3B illustrates the reservation mask shown as creating sandboxes306A, 306B, 306C in cluster 310 and allowing the autonomous cluster tostate that only a specific subset of resources can be used by theseremote requesters during a specific subset of times. When a requesterasks for resources, the scheduler will only report and return resourcesavailable within this reservation mask, after which point if the remoteentity wants to use the resources, it can actually make a consumptionreservation and that reservation is guaranteed to be within thereservation mask space. The consumption reservations 312A, 312B, 312C,312D are shown within the reservation masks.

In cluster 310 the reservation masks operate differently from consumingreservations in that they are enabled to allow personal reservations tobe created within the space that is reserved. ACL's are independentinside of a sandbox reservation or a reservation mask in that you canalso exclude other requesters out of those spaces so they dedicated forthese particular users.

The benefits of this approach include preventing local job starvation,and providing a high level of control to the cluster manager in that heor she can determine exactly when, where, how much and who can use theseresources even though the manager doesn't necessarily know who therequesters are or the combination or quantity of resources they willrequest. The administrator can determine when, how and where requestorswill participate in these grids. A valuable use is in the space ofpersonal reservations which typically involves a local user given theauthority to reserve a block of resources for a rigid time frame. Again,with a personal reservation mask, the requests are limited to only allowresource reservations within the mask time frame and mask resource set,providing again the administrator the ability to constrain exactly whenand exactly where and exactly how much of resources individual users canreserve for a rigid time frame. The individual user is not known aheadof time but it is known to the system, but it typically a standard localcluster user.

The reservation masks 306A, 306B and 306C define periodic, personalreservation masks where other reservations in a cluster 310 may becreated, i.e., outside the defined boxes. These are provisioning orpolicy-based reservations in contrast to consuming reservations. In thisregard, the resources in this type of reservation are not specificallyallocated but the time and space defined by the reservation mask cannotbe reserved for other jobs. Reservation masks enable the system to beable to control the fact that resources are available for specificpurposes, during specific time frames. The time frames may be eithersingle time frames or regular, repeating time frames to dedicate theresources to meet project needs, policies, guarantees of service,administrative needs, demonstration needs, etc. This type of reservationinsures that reservations are managed and scheduled in time as well asspace. Boxes 308A, 308B, 308C and 308D represent non-personalreservation masks. They have the freedom to be placed anywhere incluster including overlapping some or all of the reservation masks 306A,306B, 306C. Overlapping is allowed when the personal reservation maskwas setup with a global ACL. To prevent the possibility of an overlap ofa reservation mask by a non-personal reservation, the administrator canset an ACL to constrain it so that only personal consumptionreservations are inside. These personal consumption reservations areshown as boxes 312A, 312B, 312C, 312D which are constrained to be withinthe personal reservation masks 306A, 306B, 306C. The 308A, 308B, 308Cand 308D reservations, if allowed, can go anywhere within the cluster310 including overlapping the other personal reservation masks. Theresult is the creation of a “sandbox” where only personal reservationscan go without in any way constraining the behavior of the scheduler toschedule other requests. The ACL is preferably the mechanism thatconstrains which consumer or resource requests may utilize resourceswithin the reservation mask.

Another reservation type is the roll-back reservation mask shown in FIG.4. This reservation mask has particular application for enforcingpolicies or allowing support for service level guarantees in servicelevel agreements. A level of service guarantee allows a site, cluster orgrid to guarantee that a particular consumer or organization or type ofcredential is guaranteed a certain quantity of resources within acertain amount of time. The standard way to provide those guaranteeswould be to dedicate a block of resources that satisfies the needs andwould be statically and rigidly partitioned so that no one else couldaccess it. The request of that organization could not extend beyond thebounds of the dedicated block.

A self optimizing reservation will only slide forward barring resourcefailure of the actual compute resources. It does this by, when it makesa query to determine what resources are available, as part of itsalgorithm, it determines that it has availability to both free resourcesand the resources it already has reserved. In such a case in then goesand analyzes it, looks at resources that were recently freed by otherworkload and other reservations that completed early which is actuallyquite common in a cluster environment, and if it can find that it canimprove the level of service delivered to the request or it willactually create the new reservation and will remove the old reservationand adjust things as needed. A self optimizing reservation therefore hasthe ability to improve any given attribute of service to the submittingentity, community of users, administrators, etc.

With the present invention regarding the reservation roll-back, anadministrator can create a reservation mask 402 which enforces itspolicy and continues to float in time a certain distance 408 ahead ofthe current time. Typically, the rectangular area of the reservationmask has a height that corresponds to guaranteed throughput whenprocessing jobs and the horizontal distance that corresponds to thelength in time of the reservation mask. The reservation mask 402 maycorrespond to a certain amount of time according to a service levelagreement, such as 3 or 4 months for example. The reservation mask 402may extend into infinity as well if there is no defined ending time. Thereservation mask 402 is a provisioning reservation and maintains thetime offset 408 to the current time.

To illustrate the reservation roll-back, consider a service levelagreement with a company to have twenty resources available within onehour of the request for the resources and that they can make the requestanytime. The time offset 408 can then be set to one hour and the companywill never will they wait more than one hour to get up to twenty computeresources. The reservation mask 402 monitors the resources and when arequest is made for resources, consumption reservations 404 areallocated and left behind 406 as the roll-back reservation maskmaintains its offset. Those that are left behind are not “covered” bythe reservation mask 402 any longer.

An implementation with reservation rollback mask allows a site to set upbasically a floating reservation that extends from one hour in thefuture until a time further in the future, such as 4 or 8 hours in thefuture, and continues to slide forward in time. The reservation mask 402will only allow jobs from this organization into the space and can dropdown requests or reserve host resources underneath the reservation mask.As time moves forward, the reservation mask slides forward in time so italways maintains a constant distance in the future allowing theseguarantees 404 to be created and maintained 406 on the cluster.

The time offset 408 may be static or dynamic. A static offset 408 willmaintain a constant offset time, such as one hour into the future. Thestatic offset will likely be set by a service level agreement wherein acompany requests that the resources become available within an hour. Theoffset 408 may also by dynamic. There may be requests in the servicelevel agreement where under a given event or set of events, the offsetwould change wherein the reservation slides closer or farther away fromthe current time to provide a guarantee of resources within ½ (insteadof 1 hour) or 2 hours in the future. There are a variety of ways to varythe offset. One can be to simply cancel the current sliding reservationand create a new reservation at a different offset. Another way would beto maintain the current reservation but slide it closer or farther awayfrom the current time. The factors that adjust the dynamic nature of theoffset may be based on company requests, the nature and use of thecluster resources, the time the request is made, historical information,and so forth. For example, if the request for resources is made atmidnight on a Friday night, perhaps instead of the 1 hour availabilityof resources, the hosting center analyzes the cluster resources and thetime of the request and determines that it can deliver the resources in½. The company may want a flexible offset where if the request is madeduring a block of time such as between 3-4:30 pm (near the end of thework day) that the offset be shortened so that the job can be processedsooner. The modifications to the offset may be automatic based on afeedback loop of information or may be adjustable by an administrator.

The dynamic aspect of the period of time in which the reservation maskslides ahead of the current time is discussed next. This aspect of theinvention provides some flexibility in how soon resources need to beavailable after a request for a reservation. For example, if the fixedtime offset 408 is three hours, a user submits a request for areservation on Friday at 3:00 pm, the soonest the resources would beguaranteed to be available to process a submitted job is 6:00 pm. Thatmay be beyond the time that the user desires to wait to submit a job. Adynamically modifiable period of time allows for some parameters thatcan move up the period of time in which the resources can be available.

FIG. 2C illustrates the method aspect of the invention in this regard. Amethod of managing compute resources within a compute environmentcomprises establishing a policy to provide compute resources within aperiod of time from the reception of a request for a reservation (220),creating a roll-back reservation mask which slides ahead of current timeby the period of time (222) and receiving a request for a reservation,wherein the period of time by which compute resources must be availableafter a request for a reservation is dynamically modifiable (224).

The policy may be based on an agreement with a submitter of requests forreservations or a service level agreement. The period of time isdynamically modifiable based on a number of factors, such as parameterswithin the policy, events related to the compute environment (a clusterenvironment or a grid environment), historical information such asprevious jobs submitted by the submitter, events related to a timeassociated with a job submission or the job submission itself, a requestby a consumer or events related billing. As can be seen, there may be anumber of factors that may play a role in an analysis of whether theperiod of time from which resources must be available after a request isreceived may be modified (increased or decreased).

The reservation rollback policy mask is stackable allowing multipledifferent types of service or service level agreements to besimultaneously satisfied and share a collection of resources. Thisfeature is illustrated in FIG. 5. A reservation 502 is shown and cangenerally be considered as an aggregation of requests from various masks504, 506, 508 510. These are aggregated into one space 502 which willthen allow reservations to be created on a first come first serve basis,or based on other factors. If these reservation masks 504, 506, 508 and510 are stacked with individual offsets from the current time (notshown), the administrator can allow the masks to be partitioned amongconsumers. A useful component of this stackable approach is thecapability to have an enveloping reservation 502 created with a totalquantity of resource and rollback time offset 408 and a duration to theend of the SLA. Once that reservation space is established or paid for,as a service, the hosting center sub-partitions the space usingreservations to provide service guarantees, response time guarantees,quantity or resources guarantees taking advantage of the stackingcapability.

A company may therefore establish the enveloping reservation 502 andrequest from the hosting center that they partition the space accordingto various organizations within the enveloping reservation 502. Thiseliminates the need for a large entity to have its own group of clustersof computer.

Embodiments within the scope of the present invention may also includecomputer-readable media for carrying or having computer-executableinstructions or data structures stored thereon. Such computer-readablemedia can be any available media that can be accessed by a generalpurpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to carryor store desired program code means in the form of computer-executableinstructions or data structures. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or combination thereof) to a computer, the computerproperly views the connection as a computer-readable medium. Thus, anysuch connection is properly termed a computer-readable medium.Combinations of the above should also be included within the scope ofthe computer-readable media.

Computer-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. Computer-executable instructions also includeprogram modules that are executed by computers in stand-alone or networkenvironments. Generally, program modules include routines, programs,objects, components, and data structures, etc. that perform particulartasks or implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of the program code means for executing steps of the methodsdisclosed herein. The particular sequence of such executableinstructions or associated data structures represents examples ofcorresponding acts for implementing the functions described in suchsteps.

Those of skill in the art will appreciate that other embodiments of theinvention may be practiced in network computing environments with manytypes of computer system configurations, including personal computers,hand-held devices, multi-processor systems, microprocessor-based orprogrammable consumer electronics, network PCs, minicomputers, mainframecomputers, and the like. Embodiments may also be practiced indistributed computing environments where tasks are performed by localand remote processing devices that are linked (either by hardwiredlinks, wireless links, or by a combination thereof) through acommunications network. In a distributed computing environment, programmodules may be located in both local and remote memory storage devices.

Although the above description may contain specific details, they shouldnot be construed as limiting the claims in any way. Other configurationsof the described embodiments of the invention are part of the scope ofthis invention. Accordingly, the appended claims and their legalequivalents should only define the invention, rather than any specificexamples given.

I claim:
 1. A method of managing compute resources within a multi-nodecompute environment, the method comprising: identifying a need type anda group of group of available compute resources within the multi-nodecompute environment to yield identified data; based on the identifieddata, creating a non-consumption reservation mask that comprises apolicy enforcing mechanism to manage and constrain consumptionsub-reservations of compute resources covered by the non-consumptionreservation mask; and if a request from a consumer matches the needtype, then constraining a creation of a consumption sub-reservation forcompute resources such that the consumer can only use at least a portionof the compute resources covered by the non-consumption reservationmask, else, if the request does not match the need type, then notconstraining the creation of the consumption sub-reservation.
 2. Themethod of claim 1, wherein creating the non-consumption reservation maskfurther comprises specifying at least one timeframe during which thenon-consumption reservation mask enforces constraints.
 3. The method ofclaim 2, wherein the at least one time frame further comprises aplurality of independent time frames.
 4. The method of claim 2, whereinthe at least one time frame further comprises a plurality of regular,periodic timeframes.
 5. The method of claim 1, wherein need type is apersonal reservation that comprises a reservation that dedicatesresource access to at least one of a user and a group of users.
 6. Themethod of claim 5, wherein if the personal reservation provides accessto resources to a group of users, then each reservation and reservationtimeframe are determined by a user in the group of users that requeststhe respective reservation.
 7. The method of claim 1, furthercomprising: modifying the consumption sub-reservation according toreceived data.
 8. The method of claim 7, wherein the received data is atleast one of resource usage, system performance, a policy and acriterion associated with the request.
 9. The method of claim 7, whereinmodifying the consumption sub-reservation is bounded by a minimumthreshold and a maximum threshold.
 10. The method of claim 7, whereinmodifying the consumption sub-reservation further comprises modifying atleast one of: an access control list, reserved resources and a timeframe covered.
 11. The method of claim 1, further comprising: creating aset of non-consumption reservation masks covering the multiple nodes,wherein multiple consumption sub-reservations created from multipleconsumer requests are each constrained to only use at least a portion ofthe multiple nodes covered by the set of non-consumption reservationmasks.
 12. The method of claim 1, further comprising: specifying anaccess control list that constrains which consumers can utilize computeresources within the non-consumption reservation mask.
 13. The method ofclaim 1, wherein the need type comprises at least one of: a particularuse, a user, a group of users, a job source and a type of jobsubmission.
 14. A non-transitory computer-readable storage medium thatstores instructions for controlling a computing device to manage computeresources in a multi-node compute environment, the instructionscomprising: identifying a need type and a group of group of availablecompute resources within the multi-node compute environment to yieldidentified data; based on the identified data, creating anon-consumption reservation mask that comprises a policy enforcingmechanism to manage and constrain consumption sub-reservations ofcompute resources covered by the non-consumption reservation mask; andif a request from a consumer matches the need type, then constraining acreation of a consumption sub-reservation for compute resources suchthat the consumer can only use at least a portion of the computeresources covered by the non-consumption reservation mask, else, if therequest does not match the need type, then not constraining the creationof the consumption sub-reservation.
 15. The non-transitorycomputer-readable storage medium of claim 14, wherein the instructionsfurther comprise modifying the consumption sub-reservation according toreceived data.
 16. The non-transitory computer-readable storage mediumof claim 15, wherein the received data is at least one of resourceusage, system performance, a policy and a criterion associated with therequest.
 17. The non-transitory computer-readable storage medium ofclaim 15, wherein modifying the consumption sub-reservation is boundedby a minimum threshold and a maximum threshold.
 18. The non-transitorycomputer-readable storage medium of claim 14, wherein the instructionsfurther comprise: creating a set of non-consumption reservation maskscovering the multiple nodes, wherein multiple consumptionsub-reservations created from multiple consumer requests are eachconstrained to only use at least a portion of the multiple nodes coveredby the set of non-consumption reservation masks.
 19. The non-transitorycomputer-readable storage medium of claim 14, wherein the need typecomprises at least one of: a particular use, a user, a group of users, ajob source and a type of job submission.
 20. A system for managingcompute resources within a multi-node compute environment, the systemcomprising: a computer processor; a first module controlling thecomputer processor to identify a need type and a group of group ofavailable compute resources within the multi-node compute environment toyield identified data; a second module controlling the computerprocessor, based on the identified data, to create a non-consumptionreservation mask that comprises a policy enforcing mechanism to manageand constrain consumption sub-reservations of compute resources coveredby the non-consumption reservation mask; and a third module controllingthe computer processor, if a request from a consumer matches the needtype, to constrain a creation of a consumption sub-reservation forcompute resources such that the consumer can only use at least a portionof the compute resources covered by the non-consumption reservationmask, else, if the request does not match the need type, then not toconstrain the creation of the consumption sub-reservation.